Three-dimensional reconstruction of objects from shading information is a challenging task in computer vision. As most of the approaches facing the Photometric Stereo problem use simplified far-field assumptions, real-world scenarios have essentially more complex physical effects that need to be handled for accurately reconstructing the 3D shape. An increasing number of methods have been proposed to address the problem when point light sources are assumed to be nearby the target object. The proximity of the light sources complicates the modeling of the image formation as the light behaviour requires non-linear parameterisation to describe its propagation and attenuation. To understand the capability of the approaches dealing with this near-field scenario, the literature till now has used synthetically rendered photometric images or minimal and very customised real-world data. In order to fill the gap in evaluating near-field photometric stereo methods, we introduce LUCES the first real-world 'dataset for near-fieLd point light soUrCe photomEtric Stereo' of 14 objects of a varying of materials. A device counting 52 LEDs has been designed to lit each object positioned 10 to 30 centimeters away from the camera. Together with the raw images, in order to evaluate the 3D reconstructions, the dataset includes both normal and depth maps for comparing different features of the retrieved 3D geometry. Furthermore, we evaluate the performance of the latest near-field Photometric Stereo algorithms on the proposed dataset to assess the SOTA method with respect to actual close range effects and object materials.
翻译:在计算机视野中,利用阴影信息重建三维天体是一项具有挑战性的任务。光源的接近使图像形成模型更加复杂,因为光学行为要求非线性参数化来描述其传播和衰减。为了了解处理近场情景的方法的能力,迄今为止的文献使用了合成化的光学图像或最起码和非常定制化的现实世界数据。为了填补在评价近场光学立体方法方面存在的差距,我们提出了越来越多的方法来解决问题。为了填补在近场光源假定接近目标对象时存在的空白,光源的接近使图像形成模型化变得复杂,因为光学行为需要非线性参数化来描述其传播和衰减。为了了解处理这一近场情景的物体方法的能力,迄今为止的文献使用了合成化成的光学图像或最起码和非常定制的现实世界数据。为了填补在评价近场光学立体形的光学模型方法方面的空白,我们用52个LELED设备来点来点描述每个物体的近场景效果,我们用最接近3厘米的图像进行深度的深度评估,我们用最精确的图像进行实地评估,我们从地面的实地评估,用最接近3厘米的地面的图像进行实地的深度,我们用最精确的频率进行实地的图像的比。